X-ray fluorescence (XRF) spectrometry is a powerful spectroscopic technique that has been used to determine the elements that are present in a sample, and to determine the quantity of those elements in the sample. The underlying physical principle of the method is that when an atom of a particular element is irradiated with X-ray radiation, the atom ejects a core electron such as a K shell electron. The resulting atom is then in an excited state, and it can return to the ground state by replacing the ejected electron with an electron from a higher energy orbital. This is accompanied by the emission of a photon. The energy of the emitted photons is equal to the difference in the energies of the two orbitals. Each element has a characteristic set of orbital energies and therefore, a characteristic X-ray fluorescence (XRF) spectrum.
An X-ray fluorescence spectrometer is an apparatus capable of irradiating a sample with an X-ray beam, detecting the X-ray fluorescence from the sample, and using the X-ray fluorescence to determine which elements are present in the sample and measuring the quantity of these elements. A typical, commercially available energy dispersive X-ray fluorescence spectrometer is the EDAX Eagle XPL energy dispersive X-ray fluorescence spectrometer, equipped with a microfocus X-ray tube, lithium drifted silicon solid-state detector, processing electronics, and vendor supplied operating software, available from the EDAX division of Ametek, 91 McKee Drive Mahwah, N.J. 07430. An example of a wavelength dispersive X-ray fluorescence spectrometer is the ZSX Primus, available from Rigaku Americas, 9009 New Trails Drive, The Woodlands, Tex. 77381. In principle, any element may be detected and quantified with X-ray fluorescence.
More than 10% of cancer cases and up to 40% of emergency room cases involve misdiagnosis. Better analysis methods are needed. As an example, survival is associated with tumor thickness at the time of melanoma skin cancer diagnosis. The World Health Organization reports that the number of melanoma cases worldwide is increasing faster than any other cancer. An estimated 62,480 new cases and 8,420 deaths from melanoma occurred in the US in 2008. It is estimated that one in 82 people will develop melanoma in their lifetime. Melanoma has the lowest overall survival rate of any skin cancer and the prognosis for patients with metastases is extremely poor, despite a variety of therapies. Metastatic melanoma is highly resistant to current therapies. The risk of death from melanoma increases as the depth of the melanoma increases. If a melanoma is less than 1 millimeter deep, there is a slight chance that it has metastasized. Chances are greater if a melanoma has grown thicker than 1.5 millimeters, i.e. a Breslow thickness of greater than 1.5 mm Early recognition and correct prognosis of melanoma is extremely important in improving survival probability, with 10-year disease-free survival rates exceeding 90% upon early and correct diagnosis. As a second example, Autism Spectrum Disorder (ASD) and Alzheimer's Disease (AD) are thought to involve metal dyshomeostatis; however, adequate biomarkers do not exist for these diseases. Diagnoses are performed with questionnaires after symptoms have already appeared, possibly well after the time when therapies might be beneficial.
One method for estimating cancer prognosis is the use of staging-based analysis, which is the assessment of how much a cancer has spread. Staging systems account for tumor size, whether the tumor has invaded adjacent or distant organs, and whether metastases exist. The stage at the time of diagnosis is a powerful predictor of survival; although, staging methods are often inadequate. In addition, treatments are selected based on the stage of a cancer. Inadequate diagnosis, staging, prognosis, and response to therapy most assuredly harm human health. For example, the “Breslow Depth” is a technique used for the staging and prognosis of melanoma. It may help to predict the presence of lymph node metastasis. However, it is subject to several sources of error. Misdiagnosis and inadequate prognostics may cause patients to receive incorrect medications and additional invasive procedures.
Scientists are striving to find better diagnostic, prognostic, and response biomarkers. For example, prognostic factors that are either currently used or are being assessed as melanoma diagnostics/prognostics include: standard histology, immunostaining, cell type assessment and counting, Breslow depth, Clarks level, level and depth of invasion, mitotic rate, analysis of tumor-infiltrating lymphocytes, analysis of microscopic satellites. All of these face difficulties and inadequacies.
Breslow depth is measured with an ocular micrometer and requires that the entire tumor be excised; it is prone to inaccuracies and several sources of error including subjective decisions by experts, variation and uniformity of staging that is not reproducible because of variations in the depth of layers of the skin, imprecision of surgical margins, and variability in tissue samples. Distinguishing between benign lesions and melanomas is very difficult. An independent review by multiple pathologists is recommended, but agreement between pathologists is considerably variable, with disagreements in up to 40% of diagnoses as examined by panels of experienced dermatopathologists. It is particularly difficult to distinguish melanoma from sun-damaged skin. Specimens obtained using other biopsy techniques (e.g., punch biopsy) are even less accurate and can lead to sampling error. Diagnostic and management problems arise when the initial biopsy does not sample the complete skin thickness or when large lesions are not sampled adequately.
Traditional histochemical staining has been used for many years for disease diagnostics. It is performed by pathologists. Pathologist opinion of structures in stained tissue is the definitive diagnosis for most cancers and is used for prognosis, staging, therapy decisions, drug development, epidemiology, and public policy; it has been used for over 150 years and no automated method has thus far proven to be acceptable. This lack of automation leads to heavy workloads for pathologists, increased costs, and numerous errors. Although histopathologic evaluation is essential for clinical investigation, it remains a time consuming and subjective technique, with unsatisfactory levels of inter- and intra-observer discrepancy.
Mitotic Rate has been explored as a prognostic indicator for tumors such as melanoma in studies. However, mitotic rates vary even within tumors, and sampling can therefore be a major issue. Mitotic rate has been linked to tumor thickness in multivariate analysis, but remained an independent variable in other studies. Clinical usage has not proven worthy.
Mast cell participation in immune responses, tumor progression, and vascularization has been studied in vitro. However, in situ investigation of mast cells in routinely processed tissues is hampered by difficulty in reliable detection of mast cells.
The use of imaging in melanoma, in particular, ultrasound, computerized tomography, magnetic resonance imaging, and positron emission tomography is costly and error prone. Ultrasound at 20 MHz tends to overestimate melanoma Breslow thicknesses.
The existing state of the art for analyzing diseases or other abnormal states is insufficient.
There remains a need for improved methods for analyzing diseases or other abnormal states.